The DOI matches its Crossref record; 24 of the 24 references it cites were found in a registry or an index.
Role of Artificial Intelligence in Shaping Consumer Demand in E-Commerce
Open accessAbstract
The advent and incorporation of technology in businesses have reformed operations across industries. Notably, major technical shifts in e-commerce aim to influence customer behavior in favor of some products and brands. Artificial intelligence (AI) comes on board as an essential innovative tool for personalization and customizing products to meet specific demands. This research finds that, despite the contribution of AI systems in e-commerce, its ethical soundness is a contentious issue, especially regarding the concept of explainability. The study adopted the use of word cloud analysis, voyance analysis, and concordance analysis to gain a detailed understanding of the idea of explainability as has been utilized by researchers in the context of AI. Motivated by a corpus analysis, this research lays the groundwork for a uniform front, thus contributing to a scientific breakthrough that seeks to formulate Explainable Artificial Intelligence (XAI) models. XAI is a machine learning field that inspects and tries to understand the models and steps involved in how the black box decisions of AI systems are made; it provides insights into the decision points, variables, and data used to make a recommendation. This study suggested that, to deploy explainable XAI systems, ML models should be improved, making them interpretable and comprehensible.
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“This transparency and reasoning contribute to reducing abandoned products, increasing order value, and consequently boosting revenue and conversion rates, as noted [78].”
From Recent Emerging Techniques in Explainable Artificial Intelligence to Enhance the Interpretable and Understanding of AI Models for Human (2025) · cites this paper as [78]
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Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)
Adadi, A., & Berrada, M. (2018) · IEEE Access · doi:10.1109/access.2018.2870052 · Cited by 6,294
How artificial intelligence will change the future of marketing
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Can we open the black box of AI?
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Word Cloud Explorer: Text Analytics Based on Word Clouds
Heimerl, F., Lohmann, S., Lange, S., & Ertl, T. (2014) · Hawaii International Conference on System Sciences (HICSS) · doi:10.1109/hicss.2014.231 · Cited by 657
Artificial Intelligence in Business: From Research and Innovation to Market Deployment
Soni, N. R., Sharma, E. K., Singh, N., & Kapoor, A. (2020) · Procedia Computer Science · doi:10.1016/j.procs.2020.03.272 · Cited by 400
Using Wordle as a Supplementary Research Tool
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The folksonomy tag cloud: when is it useful?
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International Journal of Trend in Scientific Research and Development
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Tag clouds for summarizing web search results
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Soni, N., Sharma, E. K., Singh, N., & Kapoor, A. (2019) · RePEc: Research Papers in Economics · doi:10.48550/arxiv.1905.02092 · Cited by 163
Yi, S., & Liu, X. (2020) · Complex & Intelligent Systems · doi:10.1007/s40747-020-00155-2 · Cited by 149
Perceived Impacts of Artificial Intelligence and Responses to Positive Behaviour Change Intervention
Tussyadiah, I. P., & Miller, G. A. (2018) · Springer eBooks · doi:10.1007/978-3-030-05940-8_28 · Cited by 121
Opinion Mining on Social Media Data: Sentiment Analysis of User Preferences
Păvăloaia, V.-D., Teodor, E.-M., Fotache, D., & Danileț, M. (2019) · Sustainability · doi:10.3390/su11164459 · Cited by 81
Sentiment Analysis on Twitter Data of World Cup Soccer Tournament Using Machine Learning
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Business Intelligence: Concepts, Components, Techniques and BenefitsPreprint
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Significant Labels in Sentiment Analysis of Online Customer Reviews of Airlines
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Artificial Intelligence – Consumers and Industry Impact
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Research works printed but not linked: 2
- Kumar, 2020, The Colossal Impact of Artificial Intelligence. E-Commerce: Statistics and Facts, Int. Res. J. Eng. Technol. (IRJET), 6, 570
- Doran, D., Schulz, S., and Besold, T.R. (2017). What Does Explainable AI Really Mean? A New Conceptualization of Perspectives. arXiv, Available online: https://openaccess.city.ac.uk/id/eprint/18660/.
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Artificial intelligence (AI) applications for marketing: A literature-based study
Haleem, A., Javaid, M., Qadri, M. A., Singh, R. P., & Suman, R. (2022) · International Journal of Intelligent Networks · doi:10.1016/j.ijin.2022.08.005 · Cited by 1,364
Agentic AI: Autonomous intelligence for complex goals–a comprehensive survey
Acharya, D. B., Kuppan, K., & Divya, B. (2025) · IEEE Access · doi:10.1109/access.2025.3532853 · Cited by 717
Mathew, D. E., Ebem, D. U., Ikegwu, A. C., Ukeoma, P. E., & Dibiaezue, N. F. (2025) · Neural Processing Letters · doi:10.1007/s11063-025-11732-2 · Cited by 168
Li, G., Li, X., & Huo, L. (2023) · Heliyon · doi:10.1016/j.heliyon.2023.e12875 · Cited by 130
Hassan, N., Abdelraouf, M., & El-Shihy, D. (2025) · Future Business Journal · doi:10.1186/s43093-025-00476-z · Cited by 96
Metadata
- Authors
- Khrais, L. T.
- Affiliations
- Imam Abdulrahman Bin Faisal University (SA)
- Corresponding author
- Khrais, Laith T.
- ORCID
- Khrais, Laith T.
- Venue
- Future Internet
- Publisher
- MDPI AG
- Published
- 2020-12-08
- Volume
- 12
- Issue
- 12
- Pages
- 226
- ISSN
- 1999-5903 (ISSN-L)
- OpenAlex
- W3110686510
- Cited by
- 228
- References
- 24
- Citations by year
- 2026: 24 · 2025: 56 · 2024: 69 · 2023: 41 · 2022: 26 · 2021: 11
- FWCI
- 7.66
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Future Internet (publishedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Explainable Artificial Intelligence (XAI)
- Physical Sciences › Computer Science › Artificial Intelligence › Ethics and Social Impacts of AI
- Social Sciences › Business, Management and Accounting › Marketing › AI in Service Interactions
- Keywords
- artificial intelligence in e-commerce, consumer demand, explainable AI, explainability, ethical issues of AI, personalization, consumer behavior, black-box decision-making, interpretability, recommender systems
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